Browse Topic: Real-time data

Items (242)
In an era where automotive technology is rapidly advancing towards autonomy and connectivity, the significance of Ethernet in ensuring automotive cybersecurity cannot be overstated. As vehicles increasingly rely on high-speed communication networks like Ethernet, the seamless exchange of information between various vehicle components becomes paramount. This paper introduces a pioneering approach to fortifying automotive security through the development of an Ethernet-Based Intrusion Detection System (IDS) tailored for zonal architecture. Ethernet serves as the backbone for critical automotive applications such as advanced driver-assistance systems (ADAS), infotainment systems, and vehicle-to-everything (V2X) communication, necessitating high-bandwidth communication channels to support real-time data transmission. Additionally, the transition from traditional domain-based architectures to zonal architectures underscores Ethernet's role in facilitating efficient communication between
Appajosyula, kalyanSaiVitalVamsi
Conventional Constant Current- Constant voltage (CC-CV) based charging techniques initially consist of Constant Current (CC) phase for quick charging of the battery till it reaches the safety voltage limit wherein the Constant Voltage (CV) phase starts. Then the CV phase of the charging ensures safe charging of the battery till it is fully charged but it takes comparatively a long duration of time to the amount of charge pumped into the battery. Adoption of efficient charging algorithms are crucial for optimising the charging time, reducing the range anxiety and improving the long-term health of electric vehicle (EV) batteries. This paper proposes an innovative charging algorithm that optimises the transition from Constant Current (CC) to Constant Voltage (CV) charging stages utilising a multivariable function based on the real-time data of State-of-Charge (SoC), temperature, State-of-Health (SoH) and battery impedance parameters. By dynamically adjusting the charging parameters based
Rajawat, Shiv PratapMoorthi, SathiyaSoni, LokeshJain, Swati
ABSTRACT Information is critical to successful deployment and operation of unmanned vehicles. The increasing use of unmanned vehicles in modern conflicts has substantially increased the strategic and tactical value of these vehicles and the information they gather. It is now common public knowledge that the video streams of some predator drones were unencrypted and militants were able to use cheap commercially available software to intercept these feeds. This is an example of security as an afterthought. Encryption and security are critical to unmanned systems and should be implemented early in the development process. This paper explores some of the issues related to encryption and security of unmanned vehicles and communication
Phillips, Ramie
Tracking of energy consumption has become more difficult as demand and value for energy have increased. In such a case, energy consumption should be monitored regularly, and the power consumption want to be reduced to ensure that the needy receive power promptly. Our objective is to identify the energy consumption of an electric vehicle from battery and track the daily usage of it. We have to send the data to both the user and provider. We have to optimize the power usage by using anomaly detection technique by implementing deep learning algorithms. Here we are going to employ a LSTM auto-encoder algorithm to detect anomalies in this case. Estimating the power requirements of diverse locations and detecting harmful actions are critical in a smart grid. The work of identifying aberrant power consumption data is vital and it is hard to assure the smart meter’s efficiency. The LSTM auto-encoder neural network technique is used here for predicting power consumption and to detect anomalies
Deepan Kumar, SadhasivamArun Raj, VR, Vishnu Ramesh KumarManojkumar, R
Selective Laser Melting (SLM) has gained widespread usage in aviation, aerospace, and die manufacturing due to its exceptional capacity for producing intricate metal components of highly complex geometries. Nevertheless, the instability inherent in the SLM process frequently results in irregularities in the quality of the fabricated components. As a result, this hinders the continuous progress and broader acceptance of SLM technology. Addressing these challenges, in-process quality control strategies during SLM operations have emerged as effective remedies for mitigating the quality inconsistencies found in the final components. This study focuses on utilizing optical emission spectroscopy and IR thermography to continuously monitor and analyze the SLM process within the powder bed, intending to strengthen process control and minimize defects. Optical emission spectroscopy is employed to study the real-time interactions between the laser and powder bed, melt pool dynamics, material
Raju, BenjaminKancherla, Kishore BabuB S, DakshayiniRoy Mahapatra, Debiprosad
To help ensure that engine components are as reliable as customers need them to be, we have thus far evaluated them by establishing development target values based on market requirements, having engineers design parts to meet these requirements, then performing durability tests. These durability requirements are calculated to provide a margin of safety for use in the marketplace. However, depending on the part, these evaluation criteria can be overly aggressive against how it is used in the market, having led to a decrease in development efficiency as engine systems become more advanced. Therefore, in this study, we focused on the subject of high-cycle fatigue, which affects numerous components and is highly scalable, and built up a process for estimating the life span of components that would enable us to conduct appropriate evaluations that reflect how parts are truly used in the market. Recently, more and more vehicles are equipped with Telematics Control Units, (TCUs) which are
Tanaka, KoheiYoshii, KentaTakahashi, Katsuyuki
A tactile perception system provides human-like multimodal tactile information to objects like robots and wearable devices that require tactile data in real time. The research team developed a real-time and multi-modal tactile detection system by mimicking the principle by which various types of tactile information is perceived by a variety of sensory receptors in the human skin and is transmitted to the brain in real time
The automotive world is rapidly moving towards achieving shorter lead time using high-end technological solutions by keeping up with day-to-day advancements in virtual testing domain. With increasing fidelity requirements in test cases and shorter project lead time, the virtual testing is an inevitable solution. This paper illustrates method adopted to achieve best approximation to emulate driver behavior with 1-D (one dimensional) simulation based modeling approach. On one hand, the physical testing needs huge data collection of various parameters using sensors mounted on the vehicle. The vehicle running on road provides the real time data to derive durability test specifications. One such example includes developing duty cycle for powertrain durability testing using Road Torque Data Collection (RTDC) technique. This involves intense physical efforts, higher set-up cost, frequent iterations, vulnerability to manual errors and causing longer test lead-time. Whereas, on the other hand
Purohit, SuryakantMullapudi, DattatreyuduShevate, HemantChaskar, Mithun
In the commercial vehicle business, vehicle availability is a pivotal factor for the profitability of the customer. Nonetheless, the intricate nature of the technologies embedded in modern day engines and exhaust after-treatment systems coupled with the variability of the duty cycles of end applications of the vehicles imposes added challenges on the vehicle's sustained performance and reliability. In this context, the ability to predict potential failures through tools like telematics and real-time data analytics presents a significant opportunity for original equipment manufacturers (OEMs) to deliver distinctive value to their customers. A modern-day commercial vehicle has a minimum of 5 micro controllers managing the performance and performing the on-board diagnostics of various sub-systems like engine, after treatment system, transmission, Cab and stability controls, the driver interface, and advisory systems etc., They operate independently and also sync with each other as master
K.S, Guru PrasannaD.V, RamkumarS, KannanJ, Narayana ReddyK.R, KarthikeyanD., SomsekarM.D, SenthilkumarN, Augustin SelvakumarS.P, Suprabhan
In recent years, the automotive industry has seen an exponential increase in the replacement of mechanical components with electronic-controlled components or systems. engine, transmission, brake, exhaust gas recirculation (EGR), lighting, driver-assist technologies, etc. are all monitored and/or controlled electronically. Connected vehicles are increasingly being used by Original Equipment Manufacturers (OEMs) to collect and transmit vehicle data in real-time via the use of various sensors, actuators, and communication technologies. Vehicle telematics devices can collect and transmit data about the vehicle location, speed, fuel efficiency, State Of Charge (SOC), auxiliary battery voltage, emissions, performance, and more. This data is sent over to the cloud via cellular networks, where it can be processed and analyzed to improve their products and services by automotive companies and/or fleet management. This data can also be used for a variety of purposes, including enhancing the
Kumar, VivekZhu, DiDadam, Sumanth Reddy
The On-Board Diagnostics (OBD) system can detect problems with the vehicle’s engine, transmission, and emissions control systems to generate error codes that can pinpoint the source of the problem. However, there are several wear and tear parts (air filter, oil filter, batteries, engine oil, belt/chain, clutch, gear tooth) that are not diagnosed but replaced often or periodically in motorcycles/ power sports applications. Traditionally there is a lack of availability of in-field and on-board assistive tools to diagnose vehicle health for 2wheelers. An alert system that informs the riders about health and remaining useful life of their motorcycle can help schedule part replacements, ensuring they are always trip-ready and have a stress-free ownership and service experience. This information can also aid in the correct assessment during warranty claims. With the increase of onboard sensors on vehicles, there has been a notable increase in the availability of condition-monitoring data
Vijaykumar, SrikanthSabu, AbhijithPRADHAN, DEBAYANShrivardhankar, Yash
In order to guarantee the dependability and effectiveness of industrial machinery, real-time gearbox malfunction detection is extremely important. Traditional approaches to condition monitoring systems sometimes rely on time-consuming human inspections or routine maintenance, which can result in unanticipated failures and expensive downtime. The rise of the industrial Internet of things (IIoT) in recent years has paved the way for more sophisticated and automated monitoring methods. An IIoT-based condition monitoring system is suggested in this study for real-time gearbox failure detection. The gearbox health state is continually monitored by the system using sensor data from the gearbox, such as temperature, vibration, and oil analysis. Real-time transmission of the gathered data is made to a central monitoring hub, where sophisticated analytics algorithms are used to look for any flaws. This study’s potential to improve the dependability and operational effectiveness of industrial
Sivaraman, P.Ilakiya, P.Prabhu, M.K.Ajayan, Adarsh
With the increasing connectivity and complexity of modern automobiles, cybersecurity has become one of the most important properties of a vehicle. Various strategies have been proposed to enhance automotive cybersecurity. Digital twin (DT), regarded as one of the top 10 strategic technology trends by Gartner in 2018 and 2019, establishes digital representations in a virtual world and raises new ideas to benefit real-life objects. In this paper, we explored the possibility of using digital twin technology to improve automotive cybersecurity. We designed two kinds of digital twin models, named mirror DT and autonomous DT, and corresponding environments to support cybersecurity design, development, and maintenance in an auto’s lifecycle, as well as technique training. The mirror DT, which displays the external behaviors of the physical object, collects, displays, and analyzes real-time data, for specific purposes like security analysis, anomaly detection, and so on. The autonomous DT
Yu, JinghuaLou, ZeruHu, HongxingPu, GeguangChen, Mingsong
The automotive industry widely accepted the launch of electric vehicles in the global market, resulting in the emergence of many new areas, including battery health, inverter design, and motor dynamics. Maintaining the desired thermal stress is required to achieve augmented performance along with the optimal design of these components. The HVAC system controls the coolant and refrigerant fluid pressures to maintain the temperatures of [Battery, Inverter, Motor] in a definite range. However, identifying the prominent factors affecting the thermal stress of electric vehicle components and their effect on temperature variation was not investigated in real-time. Therefore, this article defines the vector electric vehicle thermal operating point (EVTHOP) as the first step with three elements [instantaneous battery temperature, instantaneous inverter temperature, instantaneous stator temperature]. As a next step, a novel deep learning model was proposed utilizing the integrated functions of
Kolachalama, SrikanthMalik, Hafiz
The effectiveness of obstacle avoidance response safety systems such as ADAS, has demonstrated the necessity to optimally integrate and enhance these systems in vehicles in the interest of increasing the road safety of vehicle occupants and pedestrians. Vehicle-pedestrian clearance can be achieved with a model safety envelope based on distance sensors designed to keep a threshold between the ego-vehicle and pedestrians or objects in the traffic environment. More accurate, reliable and robust distance measurements are possible by the implementation of multi-sensor fusion. This work presents the structure of a machine learning based sensor fusion algorithm that can accurately detect a vehicle safety envelope with the use of a HC-SR04 ultrasonic sensor, SF11/C microLiDAR sensor, and a 2D RPLiDAR A3M1 sensor. Sensors for the vehicle safety envelope and ADAS were calibrated for optimal performance and integration with versatile vehicle-sensor platforms. Results for this work include a
Soloiu, ValentinObando lng, DavidMehrzed, ShaenPierce, KodyWillis, JamesRowell, Aidan
The development of Digital Twin (DT) has become popular. A dominant description of DT is that it is a software representation that mimics a physical object to portray its real-world performance and operating conditions of an asset. It uses near real-time data captured from the asset and enables proactive optimal operation decisions. There are many other definitions of DT, but not many explicit evaluations of DT performance found in literature. The authors have an interest to investigate and evaluate the quality and stability of appropriate DT techniques in real world aircraft Maintenance, Repair, and overhaul (MRO) activities. This paper reviews the origin of DT concept, the evolution and development of recent DT technologies. Examples of DTs in aircraft systems and transferable knowledge in related vehicle industries are collated. The paper contrasts the benefits and bottlenecks of the two categories of DT methods, Data-Driven (DDDT) and Model-Based (MBDT) models. The paper evaluates
Wang, ChengweiFan, Ip-ShingKing, Stephen
Magna's full-vehicle expertise, systems savvy, and start-up mindset are opening new mobility markets - with extra pepperoni. Pizza is a subject that puts a smile on most faces, but for Matteo Del Sorbo, the delight extends far beyond the actual pie. “We’re having a lot of fun with this program!” exclaimed Del Sorbo, the executive VP at Magna International and global lead for the Tier 1's New Mobility enterprise, in an interview with SAE Media. “It's demonstrating our ability to innovate and move fast. And it's opening another new market that we very much want to play in
Brooke, Lindsay
The demand for contactless, rapid manufacturing has increased over the years, especially during the COVID-19 pandemic. Additive manufacturing (AM), a type of rapid manufacturing, is a computer-based system that precisely manufactures products. It proves to be a faster, cheaper, and more efficient production system when integrated with cloud-based manufacturing (CBM). Similarly, the need for semiconductors has grown exponentially over the last five years. Several companies could not keep up with the increasing demand for many reasons. One of the main reasons is the lack of a workforce due to the COVID-19 protocols. This article proposes a novel technique to manufacture semiconductor chips in a fast-paced manner. An algorithm is integrated with cloud, machine vision, sensors, and email access to monitor with live feedback and correct the manufacturing in case of an anomaly. Several real-time data such as performance graphs, time left, and other current information were sent back to the
Viswanath, ShreyaSiddharth, S.Subramanian, Jeyanthi
Kontron and Intel experts explain how rugged, modular COM Express solutions reduce complexity and allow retrofit of autonomous systems on heavy mobile equipment. Continually transformed with more than a century's advances in capabilities, hydraulics and fuel efficiency, today's heavy mobile equipment must also become more intelligent and better connected. Technologies such as artificial intelligence (AI), deep learning, big data, GPS, 5G and computer vision are proving their mettle - empowering far more efficient ways of carrying out unique and demanding tasks via advanced telematics, advanced driver assistance systems (ADAS) or varying levels of autonomy. Heavy mobile equipment (HME) that can gather and apply data in real time operates and makes decisions in ways that humans cannot. This evolution toward automation promises not only leadership for manufacturers of more advanced systems, but also increased safety, economy, efficiency and ecological compatibility
London, JackThomas, Andrea
The purpose of the OBIGGS is to reduce the amount of oxygen in the fuel tank to a 'safe' level to significantly reduce the possibility of ignition of fuel vapors. There are circumstances where equipment of OBIGGS like ASMs, Ozone Converter Catalysts, etc. gets degraded earlier than the provided MTBF. This paper studies the present conventional systems limitations, like due to memory constraints only the faults and limited shop data are being recorded, hence there is no provision to store/report the stream of data margins with which we can pass/fail the performance tests. This paper also explains how a new design of the Connected concept achieves access to real-time data from the system and how the data is pushed to the cloud network. A connected solution for the OBIGGS is the technology to access real-time data (Systems LRUs Performance data and Custom data Parameters) from the Systems controller data bus, this data is further applied to AI/ML methods for predictive/prognostics
Kumar, NaveenKotnadh, ShivaprasadMorkondaHaribapu cEng, ArvindKanneboyina cEng, RajeshRao cEng, Manjunatha
Air Cargo is one of the major modes of cargo transportation in the world. It is helping to transport goods swiftly across the globe during emergencies like pandemic, evacuation, and natural calamities etc. It plays a key role in economy of a country by exporting and importing goods across the globe. This business is growing every YOY with increase in demand for e-Commerce and globalization. It is also important to keep up the efficiency of the system as the business demand grows. This paper focuses on Artificial Intelligence (AI) implementation can reduce the inefficiency and inconsistency due to the manual intervention in cargo operation in different areas. The major Implementation study area of AI in this paper include implementing in Cargo load planning to reduce the human dependency and error, ground handling with the help of autopiloting vehicle which can operate in any weather condition, sequence of loading Unit Load Devices (ULD’s) based on priority, operating control unit to
Chitragar, VenkateshAdavalath Puthiyaveettil, SayoojVijaya Chandran, VinayakGopan, Vishnu
Engineers have created a flexible electronic sensing patch that can be sewn into clothing to analyze sweat for multiple markers. The patch could be used to diagnose and monitor acute and chronic health conditions or to monitor health during athletic or workplace performance. The device consists of special sensing threads, flexible electronic components, and wireless connectivity for real-time data acquisition, storage, and processing
Operational Technology (OT) networks are historically “air-gapped” from the rest of the networked world. But pressure is mounting for manufacturers to leverage real-time data exchanges from outside their controlled environments to increase productivity and efficiency. One major concern for manufacturers is how safe and secure it is to open the OT network’s doors to the internet
The integration of sensors, actuators, and real-time control in transportation systems enables intelligent system operation to minimize energy consumption and maximize occupant safety and vehicle reliability. The operating cycle of military ground vehicles can be on- and off-road in harsh weather and adversarial environments, which demands continuous subsystem functionality to fulfill missions. Onboard diagnostic systems can alert the operator of a degraded operation once established fault thresholds are exceeded. An opportunity exists to estimate vehicle maintenance needs using model-based predicted trends and eventually compiled information from fleet operating databases. A digital twin, created to virtually describe the dynamic behavior of a physical system using computer-mathematical models, can estimate the system behavior based on current and future operating scenarios while accounting for past effects. In this manner, the collection of real-time data of the physical vehicle can
Eddy, ConnerWagner, AdamWagner, JOHNCastanier, Matthew P.
Photoscanning photogrammetry is a method for obtaining and preserving three-dimensional site data from photographs. This photogrammetric method is commonly associated with small Unmanned Aircraft Systems (sUAS) and is particularly beneficial for large area site documentation. The resulting data is comprised of millions of three-dimensional data points commonly referred to as a point cloud. The accuracy and reliability of these point clouds is dependent on hardware, hardware settings, field documentation methods, software, software settings, and processing methods. Ground control points (GCPs) are commonly used in aerial photoscanning to achieve reliable results. This research examines multiple GCP types, flight patterns, software, hardware, and a ground based real-time kinematic (RTK) system. Multiple documentation and processing methods are examined and accuracies of each are compared for an understanding of how capturing methods will optimize site documentation
Mckelvey, NathanKing, CharlesTerpstra, TobyHashemian, AlirezaMitchell, Steven
In the automotive industry, a Malfunction Indicator Light (MIL) is commonly employed to signify a failure or error in a vehicle system. To identify the root cause that has triggered a particular fault, a technician or engineer will typically run diagnostic tests and analyses. This type of analysis can take a significant amount of time and resources at the cost of customer satisfaction and perceived quality. Predicting an impending error allows for preventative measures or actions which might mitigate the effects of the error. Modern vehicles generate data in the form of sensor readings accessible through the vehicle’s Controller Area Network (CAN). Such data is generally too extensive to aid in analysis and decision making unless machine learning-based methods are used. This paper proposes a method utilizing a recurrent neural network (RNN) to predict an impending fault before it occurs through the use of CAN data. Methods to pre-process the vehicle data for dimensionality reduction
Hulbert, ScottMollan, CalahanPandey, Vijitashwa
This paper deals with stability of motion and its criteria for tracking control of intelligent vehicle systems. It deals with general control structure and specification of an optimum range of predefined control parameters for accurate tracking of these vehicle systems. A two degree of freedom (DOF) nonlinear dynamic model is developed to represent their plane motion. This model is further utilized in deriving a linear model that is used to do this stability analysis. Path tracking of the vehicle is attained by controlling the position and orientation errors about a predefined trajectory, which is accomplished by modifying the steering input signal on the basis of error feedbacks to the controller. Establishing the general structure of the controller through the design of an optimal controller, applying various stability criteria, and other constraints such as applying the physical limits of the vehicle to the controlled system narrows down the range of control parameters, within which
Kuttolamadom, MathewMehrabi, Mostafa
Mechanical systems accomplish their tasks better when enhanced with cyber technologies. With the rapidly escalating desire for high efficiency, optimization and flexibility, these physical systems ought to be integrated with cyber technologies that enhance exhaustive manipulation of resources and productivity. The gateway for such a synergetic integration can be referred to as digitalization. Details regarding the digitization of a High-altitude Simulation chamber are discussed thoroughly in this paper. The simulation chamber was originally designed and developed as a test bench to study the characteristics of alternative fuels used in the engines of handheld tools in different altitudes and thermal conditions. It encompasses all the possible realistic temperature variations with altitude raising to 3500m above sea level. Since the testbed’s effectiveness is highly dependent on achieving a combination of desired temperature and altitude values to maintain them for a defined period
Derbie, ArsemaNenninger, PhilippHadamek, ChristofRenner, MariusKettner, MauriceAslan, FerhatWoldesenbet, Eyassu
This SAE Aerospace Information Report (AIR) provides a review of real-time modeling methodologies for gas turbine engine performance. The application of real-time models and modeling methodologies are discussed. The modeling methodologies addressed in this AIR concentrate on the aerothermal portion of the gas turbine propulsion system. Characteristics of the models, the various algorithms used in them, and system integration issues are also reviewed. In addition, example cases of digital models in source code are provided for several methodologies
S-15 Gas Turbine Perf Simulation Nomenclature and Interfaces
The purpose of this standard is to aid manufacturers in creating devices that will provide maintenance staff with objective, reliable data consistent with certain types of airborne contaminants (“sources”), captured either during an event or during maintenance troubleshooting on the ground, in both cases for post-flight interpretation on the ground
AC-9M Cabin Air Measurement Committee
In the past years, the automotive industry has been integrating multiple hardware in the vehicle to enable new features and applications. In particular automotive applications, it is important to monitor the actions and behaviors of drivers and passengers to promote their safety and track abnormal situations such as social disorders or crimes. These applications rely on multiple sensors that generate real-time data to be processed, and thus, they require adequate data acquisition and analysis systems. This article proposes a prototype to enable in-vehicle data acquisition and analysis based on the middleware framework Robot Operating System (ROS). The proposed prototype features two processing devices and enables synchronized audio and video acquisition, storage, and processing. It was assessed through the implementation of a live inference system consisting of a face detection algorithm from the data gathered from the cameras and the microphone. The proposed prototype inherits the
Oliveira, AnaFonseca, JoaquimPinto, Pedro
In 1901, a patent was issued to Ransom E. Olds for the idea of a continuously moving assembly line, which he used to build the first Oldsmobile vehicles. In 1913, Henry Ford improved the concept by adding moving conveyor belts and with these two innovations, the time needed to assemble a car went from 1½ days to 1½ hours. The modern assembly factory was born
The U.S. Food and Drug Administration’s (FDA) multifaceted responsibilities require continuous monitoring of trends in science and technology for the advancement of public health. In early 2020, the agency saw investigational new drug (IND) applications skyrocket to 3,806 — a significant increase compared to the previous year when they received only 166 applications during the same months.1
Manufacturing automation is now well into the Industry 4.0 era. New machine control and drive technologies are rapidly being introduced to provide more flexibility and productivity as well as smarter, more sophisticated use of real-time, actionable data on machine performance
The bottom of a lake or an ocean is an ever-changing place. Water flows back and forth in shifting currents. Sunlight heats the sand and darkness cools it back down. The sand itself moves, unveiling rocks and man-made objects of peculiar shape underneath
Now-a-days, Advanced driver-assistance systems (ADAS) is equipping cars and drivers with advance information and technology to make them become aware of the environment and handle potential situations in better way semi-autonomously. High-quality training and test data is essential in the development and validation of ADAS systems which lay the foundation for autonomous driving technology. ADAS uses the technology like radar, vision and combinations of various sensors including LIDAR to automatize dynamic driving tasks like steering, braking, and acceleration of vehicle for controlled and safe driving. And to integrate these advance technologies, the ADAS needs labeled data to train the algorithm to detect the various objects and moments of driver. Image annotation is one the well-known service to create such training data for computer vision. There are number of open source annotated datasets available viz. COCO, KITTI etc. But these datasets are limited to either US or European road
Pachhapurkar, NinadShah, RathinKale, JyotiKarle, ManishKarle, Ujjwala
This SAE Aerospace Recommended Practice (ARP) provides insights on how to perform a Cost Benefit Analysis (CBA) to determine the Return on Investment (ROI) that would result from implementing a blockchain solution to a new or an existing business process. The word “blockchain” refers to a method of documenting when data transactions occur using a distributed ledger with desired immutable qualities. The scope of the current document is on enterprise blockchain which gives the benefit of standardized cryptography, legal enforceability and regulatory compliance. The document analyzes the complexity involved with this technology, lists some of the different approaches that can be used for conducting a CBA, and differentiates its analysis depending on whether the application uses a public or a private distributed network. This document is intended for people who do not have a deep technical understanding or familiarity with blockchain solutions to qualify and quantify its economic benefits
G-31 Digital Transactions for Aerospace
For as long as there has been warfare, military field commanders have tried to extend their range of vision, gather and interpret critical intelligence, and gain strategic and tactical advantages through real-time, uncompromised communications
In the final few minutes of a spacecraft landing, it is moving at hypersonic speed through many layers of atmosphere. Knowing the air density outside the vehicle can have a substantial effect on its angle of descent and ability to hit a specific landing spot. But air density sensors that can withstand the harsh hypersonic conditions are uncommon. Researchers developed an algorithm that can run onboard a vehicle, providing important real-time data to aid in steering the craft, particularly during the crucial entry, descent, and landing stage
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